Common strategy to improve community detection performance based on the nodes' property. Issue 2 (25th April 2019)

• Record Type: Journal Article
• Authors: Du, Wei; He, Xiaochen
• Is Part Of: CAAI transactions on intelligence technology. Volume 2:Issue 2(2017)
• Page Start: 68
• Page End: 72
• Publication Date: 2019-04-25
• Subjects: network theory (graphs) -- graph theory -- social networking (online) -- pattern clustering -- complex networks; common strategy -- community detection performance -- nodes -- community detection algorithm -- detected community structure -- community signals -- community sign change -- communities -- modularity value; Artificial intelligence -- Periodicals; Computer science -- Periodicals; Artificial intelligence; Computer science; Electronic journals; Periodicals; 006.305
• DOI: 10.1049/trit.2017.0003
• Languages: English
• ISSNs: 2468-6557

Abstract

Abstract : Improving the community detection algorithm is of great importance. The authors propose a novel method based on the nodes' property in order to detect the community structure. Given a detected community structure, in which nodes have their community signals, the value of the modularity can be changed if a node's community sign change to other communities' signs. Accordingly, the new method readjusts the affiliation between a node and its community in order to raise the modularity value. Experimental results of the detection for a list of open‐source networks show that the proposed algorithm can detect better community structure than classic methodologies based on modularity.